Temporal primacy overrides prior training in serial compound conditioning of the rabbit’s nictitating membrane response

Kehoe, E. James; Schreurs, Bernard G.; Graham, Peita

doi:10.3758/bf03205056

Cited by 60 publications

(43 citation statements)

References 31 publications

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“…5c), but not an outright absence of blocking. Responding to the pretrained CSA, in contrast, showed progressive declines after CSB was added in eyeblink and fear conditioning (Cole & McNally, 2007;Kehoe et al, 1987), consistent with the presence representation, but not in appetitive conditioning (Jennings & Kirkpatrick, 2006), more consistent with the CSC and MS representations.…”

Section: Cue Competition Setmentioning

confidence: 78%

“…In the empirical data, when the onset of the added CSB occurred earlier than the pretrained CSA, responding to the added CSB showed little evidence of blocking (Amundson & Miller, 2008, Experiment 2;Cole & McNally, 2007;Jennings & Kirkpatrick, 2006, Experiment 2;Kehoe et al, 1987). Independently of stimulus representation, the TD model correctly predicts attenuated blocking of responding to CSB in this situation (Fig.…”

Section: Cue Competition Setmentioning

confidence: 98%

“…Although an obvious simplification, this approach, in combination with an appropriate learning rule, can accomplish a surprisingly wide range of real-time learning phenomena (Sutton & Barto, 1981, 1990). Sutton and Barto (1990) demonstrated that the TD learning rule, in conjunction with this stimulus representation, was sufficient to reproduce the effects of interstimulus interval (ISI) on the rate of acquisition, as well as blocking, second-order conditioning, and some temporal primacy effects (e.g., Egger & Miller, 1962;Kehoe, Schreurs, & Graham, 1987). This presence representation suffers from the obvious fault that there is complete generalization (or a lack of temporal differentiation) across all time points in a stimulus.…”

Section: Presence Representationmentioning

confidence: 99%

“…Thus, in the resulting compound, the onset of the added, blocked stimulus (CSB) occurred at the same time, later, or earlier than the blocking stimulus (CSA) (cf. Jennings & Kirkpatrick, 2006;Kehoe, Schreurs, & Amodei, 1981;Kehoe et al, 1987). In the simulations, CSA was first trained individually for 200 trials, and then CSA and CSB were trained in compound for a further 200 trials.…”

Section: Cue Competition Setmentioning

confidence: 99%

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Evaluating the TD model of classical conditioning

2012

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The temporal-difference (TD) algorithm from reinforcement learning provides a simple method for incrementally learning predictions of upcoming events. Applied to classical conditioning, TD models suppose that animals learn a real-time prediction of the unconditioned stimulus (US) on the basis of all available conditioned stimuli (CSs). In the TD model, similar to other error-correction models, learning is driven by prediction errors-the difference between the change in US prediction and the actual US. With the TD model, however, learning occurs continuously from moment to moment and is not artificially constrained to occur in trials. Accordingly, a key feature of any TD model is the assumption about the representation of a CS on a moment-to-moment basis. Here, we evaluate the performance of the TD model with a heretofore unexplored range of classical conditioning tasks. To do so, we consider three stimulus representations that vary in their degree of temporal generalization and evaluate how the representation influences the performance of the TD model on these conditioning tasks.Keywords Associative learning . Classical conditioning . Timing . Reinforcement learning Classical conditioning is the process of learning to predict the future. The temporal-difference (TD) algorithm is an incremental method for learning predictions about impending outcomes that has been used widely, under the label of reinforcement learning, in artificial intelligence and robotics for real-time learning (Sutton & Barto, 1998). In this article, we evaluate a computational model of classical conditioning based on this TD algorithm. As applied to classical conditioning, the TD model supposes that animals use the conditioned stimulus (CS) to predict in real time the upcoming unconditioned stimuli (US) (Sutton & Barto, 1990). The TD model of conditioning has become the leading explanation for conditioning in neuroscience, due to the correspondence between the phasic firing of dopamine neurons and the reward-prediction error that drives learning in the model (Schultz, Dayan, & Montague, 1997; for reviews, see Ludvig, Bellemare, & Pearson, 2011;Maia, 2009;Niv, 2009;Schultz, 2006).The TD model can be viewed as an extension of the Rescorla-Wagner (RW) learning model, with two additional twists (Rescorla & Wagner, 1972). First, the TD model makes real-time predictions at each moment in a trial, thereby allowing the model to potentially deal with intratrial effects, such as the effects of stimulus timing on learning and the timing of responses within a trial. Second, the TD algorithm uses a slightly different learning rule with important implications. As will be detailed below, at each time step, the TD algorithm compares the current prediction about future US occurrences with the US predictions generated on the last time step. This temporal difference in US prediction is compared with any actual US received; if the latter two quantities differ, a prediction error is generated. This prediction error is then used to alter the associative ...

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Section: Cue Competition Setmentioning

confidence: 78%

Section: Cue Competition Setmentioning

confidence: 98%

Section: Presence Representationmentioning

confidence: 99%

Section: Cue Competition Setmentioning

confidence: 99%

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Evaluating the TD model of classical conditioning

2012

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“…Although they routinely predict antieipatory CRs, these models do not concern themselves with the exact time course of theCR. These models have been suecessful in explaining and even truly predicting interactions among serial stimuli (Kehoe, Schreurs, & Graham, 1987). It remains for a more detailed account of the CR's time course to be developed in these models.…”

Section: Learning Rulesmentioning

confidence: 99%

Real-time factors in the rabbit’s nictitating membrane response to pulsed and serial conditioned stimuli

Kehoe

Napier

1991

Animal Learning & Behavior

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Conditioning theories and recent real-time models commonly postulate that a reinforcer is signaled by aseries of stimuli. In both Pavlovian and operant procedures, serial stimuli have heen shown to control the likelihood and timing of responses over intervals of seconds and minutes. The present experiments were conducted to determine whether serial stimuli exercise similar effects over stimulus-reinforcer intervals in the order of hundreds of milliseconds. Such intervals typify those used in conditioning of the rabbit nictitating membrane response. A sequence of four tone pulses (50-100 msec) was used as the CS to assess the effectiveness of serial stimuli. After training with this CS, tests were conducted in which one or more of the pulses were removed. These perturbations of the sequence of stimuli over a 400-msec interval produced large deficits in CR likelihood and smaller alterations in CR timing. The results are discussed with respect to their implications for current real-time models of conditioning, and particularly with respect to their assumptions about the source of internal stimuli, rules for learning, and rules for generating CRs.

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Fundamental Behavioral Methods and Findings in Classical Conditioning

Kehoe

Macrae²

2002

A Neuroscientist’s Guide to Classical Conditioning

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Temporal primacy overrides prior training in serial compound conditioning of the rabbit’s nictitating membrane response

Cited by 60 publications

References 31 publications

Evaluating the TD model of classical conditioning

Evaluating the TD model of classical conditioning

Real-time factors in the rabbit’s nictitating membrane response to pulsed and serial conditioned stimuli

Fundamental Behavioral Methods and Findings in Classical Conditioning

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